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Minimizing Systematic Errors in Quantitative High Throughput Screening Data Using Standardization, Background Subtraction, and Non-Parametric Regression
Quantitative high throughput screening (qHTS) has the potential to transform traditional toxicological testing by greatly increasing throughput and lowering costs on a per chemical basis. However, before qHTS data can be utilized for toxicity assessment, systematic errors such as row, column, cluste...
Enregistré dans:
| Publié dans: | J Exp Second Sci |
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| Auteurs principaux: | , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2014
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5102623/ https://ncbi.nlm.nih.gov/pubmed/27840777 |
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